Advances in Image-Based Strategies for the Early Detection of Amelanotic Melanoma: Clinical Validation and International Perspectives
DOI:
https://doi.org/10.64784/070Palabras clave:
Amelanotic melanoma, early detection, dermoscopy, image-based diagnosis, clinical validation, melanoma screening, diagnostic support systems, multimodal assessmentResumen
Amelanotic melanoma represents a diagnostically challenging subtype of melanoma due to the absence or minimal presence of pigmentation, which often leads to delayed recognition and poorer clinical outcomes. Early detection is therefore critical, yet traditional visual and dermoscopic criteria demonstrate limited sensitivity for non-pigmented lesions. In recent years, advanced image-based diagnostic approaches have shown promising performance in melanoma detection; however, their applicability to amelanotic melanoma and their validation across diverse clinical contexts remain insufficiently explored. This review analyzes current evidence on image-based strategies for the early detection of amelanotic melanoma, focusing on diagnostic performance, clinical validation, and integration into real-world practice. A structured narrative review methodology was employed, synthesizing findings from comparative performance studies, clinical validation trials, benchmarking initiatives, and meta-analyses. The results indicate that while image-based approaches can enhance diagnostic sensitivity and support clinician decision-making, their effectiveness is strongly influenced by dataset representation, lesion subtype complexity, and clinician–system interaction. Evidence further supports the value of multimodal diagnostic pathways that integrate clinical evaluation, dermoscopy, image-based analysis, and adjunctive imaging in diagnostically ambiguous cases.
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